118 | | where \(N(\delta\theta)\) is the number of produced events in the interval \(\delta\theta\) and \(\Delta T(\delta\theta)\) is the total observation time in the same zenith angle interval. \(\tau_0\) is the normalization constant. |
119 | | |
120 | | \[\sigma^2(\tau_i) = \left[\frac{d\tau_i}{d\Delta T_i}\sigma(\Delta T_i)\right]^2+\left[\frac{d\tau_i}{dN_i}\sigma(N_i)\right]^2= \tau_i^2\cdot\left[\left(\frac{\sigma(\Delta T_i)}{\Delta T_i}\right)^2+\left(\frac{\sigma(N_i)}{N_i}\right)^2\right]\] |
121 | | |
122 | | While \(\sigma(\Delta T_i)/\Delta T_i \approx 1\textrm{s}/5\textrm{min}\) is given by the data acquisition and 1s per 5min run, \(\sigma(N_i)/N_i=1/\sqrt{N_i}\) is just the statistical error of the number of events. |
| 118 | where \(N(\delta\theta)\) is the number of produced events in the interval \(\delta\theta\) and \(\Delta T(\delta\theta)\) is the total observation time in the same zenith angle interval. \(\tau_0\) is the normalization constant. The error on the weight \(\tau=\tau(\delta\theta)\) in each individual \(\theta\)-bin with \(\Delta T=\Delta T(\delta\theta)\) and \(N=N(\delta\theta\)is then |
| 119 | |
| 120 | \[\sigma^2(\tau) = \left[\frac{d\tau}{d\Delta T}\sigma(\Delta T)\right]^2+\left[\frac{d\tau}{dN}\sigma(N)\right]^2= \tau^2\cdot\left[\left(\frac{\sigma(\Delta T)}{\Delta T}\right)^2+\left(\frac{\sigma(N)}{N}\right)^2\right]\] |
| 121 | |
| 122 | While \(\sigma(\Delta T)/\Delta T \approx 1\textrm{s}/5\textrm{min}\) is given by the data acquisition and 1s per 5min run, \(\sigma(N)/N=1/\sqrt{N}\) is just the statistical error of the number of events. |